Female Picks:
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1. Big Apple Brunch | Hell's Kitchen | 9.2/10
2. Pietro Nolita | Nolita | 8.6/10
3. Kanü Bar|Grill | Hamilton Heights | 8.5/10
4. STK Steakhouse Downtown | West Village | 8.2/10
5. Lighthouse Fish Market | East Harlem | 8.2/10
Male Picks:
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1. Lahori Kabab | Kips Bay | 2.3/10
2. Big Arc Chicken | East Village | 2.5/10
3. Hop Won Express | Midtown East | 3.1/10
4. Subway | Hell's Kitchen | 3.1/10
5. Nica Trattoria | Upper East Side | 3.1/10
I think there's a category of these kinds of things where you apply AI to do something humans could do, but could not be bothered to do. Or could not profitably do. At least no human would categorize all these reviews just for lols.
Another recent example from HN would be that site which just lists hotel rooms that have a desk and a chair. It would be an incredibly dull task for a human to look at a million hotel room pictures and just select if they have a desk or not.
What else somewhat useful/fun could we do applying perhaps a little worse than human attention at something, but a lot of it?
took only a few checks for me to come to the conclusion that the setup has the age-old heavy bias towards beauty standards. I.e., if customers are black or Asian, hotness ranking goes down.
23 comments
[ 0.22 ms ] story [ 36.2 ms ] threadDoes anyone do this for a restaurants? That's not something that ever really factored into my food habits
Any details on how you managed to scrape the all mighty goog?
I assume it's a racial thing and the AI could not really detect the age correctly?
In NY the Irish pubs are tagged as old, which kinda makes sense.
I am here for it. I want more of this.
This feels oddly old school shit posty made reality
Another recent example from HN would be that site which just lists hotel rooms that have a desk and a chair. It would be an incredibly dull task for a human to look at a million hotel room pictures and just select if they have a desk or not.
What else somewhat useful/fun could we do applying perhaps a little worse than human attention at something, but a lot of it?
This sucks.
The Map Rating Restaurants Based on How Hot the Customers Are
https://www.nytimes.com/2025/07/01/dining/looksmapping-hot-c... (https://archive.ph/3ItEb) (https://news.ycombinator.com/item?id=44444973)
That cluster coincides with Harlem which has a majorly Black and Hispanic population and (I think) is generally lower-wealth.
Unintentional race and/or wealth/class bias in the model exposed here?